The field of pattern recognition for the purpose of image alignment, inspection and verification has wide application in industry. For example, in the highly automated fabrication of integrated circuits, many manufacturing processes demand the accurate optical registration of circuit patterns as a prerequisite step.
It is known that the gray scale characteristics of an image of a scene can change as a result of complex parameters related to variability of both the illumination source, and as a result of the optical characteristics of the material in the field of view. Some of these parameters are relatively easy to predict and model mathematically. It is known, for example, that invariance to global linear intensity variation can be provided by use of a gray scale normalized correlation image similarity metric. Likewise, the Generalized Hough Transform (GHT), which is based on the accumulation of a count of matching edge gradient direction, is known to provide intensity normalization on a pixel neighborhood basis. Syntactic analysis groups local neighborhood computed edge gradient features into high-level components, such as lines, corners, and arc segments, to construct a graph-like data structure that is used to search for a best-match pattern consistent with the model syntax.
Each of the aforementioned techniques has advantages and disadvantages. Normalized correlation metric search is easy to train and it can be efficiently implemented on inexpensive high-speed hardware, but it suffers from the inability to generalize beyond simple linear intensity variation. Generalized Hough Transform search is substantially invariant to non-linear gray scale image variation, but GHT tends to over-generalize. Additionally, the GHT method requires a computationally expensive pre-processing step to compute edge magnitude and direction information, and a large high-speed memory array to accommodate the fan-out nature of the accumulation algorithm. Syntactic approaches typically require a high degree of supervision during the training process, and are in general too complex for practical applications in, for example, semiconductor test equipment.